Entry Level Science Jobs in Austin, TX (NOW HIRING)

At Four Hands, technology and data are key drivers of how we serve our customers and grow our business. As an Entry Level Data Engineer, you'll help build and support the data pipelines, integrations, and automated workflows that power our eCommerce, inventory, fulfillment, analytics, and customer experience teams.

You'll work alongside experienced team members across Data, Application Development, Cloud, and IT Operations, gaining hands-on experience with the systems and technologies that move and transform data across the organization. From building ETL pipelines and working with enterprise data sources to improving data quality and supporting analytics, you'll contribute to real projects from the start.

We're building an automation- and data-first mindset across our technology organization and are looking for someone who is curious about how data moves, how systems connect, and how reliable data can help teams make better decisions. This is an opportunity to develop your technical skills, learn modern data engineering practices, and help build the data foundation that will support analytics, automation, and AI capabilities across Four Hands.

Authorization

• Candidates must be legally authorized to work in the United States on a full-time basis now and in the future.
• Visa sponsorship is not available for this role.

Location

• This is a hybrid role based in Austin, TX, with an expectation of working in the office Monday, Tuesday, and Thursday each week.
• Candidates must be located in or willing to relocate to the Austin area. Relocation assistance is not available for this position.

In This Role

• Build, maintain, and support data pipelines and ETL/ELT processes that move and transform data across enterprise systems, databases, and cloud environments.
• Write SQL queries to extract, transform, validate, and analyze data while developing an understanding of relational data models and schemas.
• Use Python and other scripting languages to automate data processing, validation, and repetitive workflows.
• Help integrate data from enterprise systems such as ERP, WMS, CRM, eCommerce, and other internal and third-party platforms.
• Monitor data pipelines and troubleshoot issues related to data quality, failed jobs, missing records, or unexpected results.
• Develop data validation and quality checks to help ensure information used for reporting, analytics, automation, and AI is accurate, complete, and consistent.
• Work with APIs, JSON/XML, webhooks, and other integration methods to ingest and exchange data between systems.
• Collaborate with analysts, engineers, and business teams to understand data requirements and translate them into reliable technical solutions.
• Help document data sources, transformations, schemas, dependencies, and pipeline processes so our data environment remains understandable and maintainable.
• Contribute to CI/CD pipelines, version control, testing, and deployment practices for data engineering workloads.
• Gain hands-on experience with cloud data and integration technologies such as Azure Data Factory, Azure Functions, Logic Apps, Service Bus, and related Azure services.
• Support the development of reliable data foundations that enable future analytics, machine learning, automation, and AI initiatives.
• Other duties as assigned, in accordance with training and qualifications.
• Uphold our core values and be a valuable member of the Four Hands team:
  • Be open and honest
  • Reach for excellence
  • Act with responsibility
  • Value the whole person
  • Enjoy the journey

The Ideal Person

• Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, Statistics, or a related technical field, or equivalent experience.
• Foundational programming skills, with Python strongly preferred.
• Experience with SQL and relational databases through coursework, internships, personal projects, or professional experience.
• Basic understanding of database concepts, including tables, schemas, joins, primary and foreign keys, and data relationships.
• Exposure to ETL/ELT, data pipelines, data transformation, or data integration through coursework, internships, projects, or professional experience.
• An interest in understanding how data moves between systems and how reliable data supports analytics and business decision-making.
• Familiarity with version control tools such as Git and a willingness to learn CI/CD and modern data engineering practices.
• Exposure to cloud platforms such as Azure, AWS, or GCP is a plus but not required.
• Experience with tools such as Azure Data Factory, Databricks, Snowflake, dbt, Airflow, or similar data technologies is a plus but not required.
• A problem-solver and self-starter who enjoys investigating data issues, learning how systems work, and finding ways to make processes more reliable and efficient.
• Strong communication skills with the ability to collaborate with both technical and non-technical teammates.
• Eagerness to learn and grow within data engineering while contributing to production systems and real-world business problems.